1. Field of the Invention
The present invention relates to an image processing apparatus capable of associating a subject at a high speed when a plurality of images are combined.
2. Description of the Related Art
The conventional image processing method is described below with reference to FIGS. 1 through 5.
For example, assume that the images as shown in FIG. 1 (a) and FIG. 1(b) are superposed one on the other as shown in FIG. 1 (c). In this case, as shown in FIG. 2, the feature point of one image is extracted, the other image is searched for the feature point, and the subjects are associated with each other. At this time, if the feature point is traced using the original image as is, it is necessary to search for the feature points of the entire original image as shown in FIG. 3. Therefore, the search range is large. A common method of avoiding this problem is to first associate feature points at low resolution as shown in FIGS. 5 ((1a) and (1b)), raise the resolution stepwise with the feature point search range limited at an image with higher resolution (FIG. 5 (2a) through (3b)). The patent document 5 describes a method of raising the resolution with the search range limited sequentially using results obtained with images with lower resolution to combine two images partly overlapping each other. There is a method of extracting a feature point by first extracting a feature point from an original image of high resolution and obtaining a point corresponding to the feature point as a feature point of a reduced image, and a method of extracting a feature point from a reduced image.
FIG. 4 shows the concept of an image including a feature point and an image including no feature point. A feature point refers to a point at which edges cross each other or at which curvature of an edge is large as indicated by the arrows shown in FIGS. 4 (a) and (b). Since FIG. 4(c) and FIG. 4(d) do not include a point of high curvature or a point at which edges cross each other, they do not include a feature point. There are operators such as Moravec, Harris, SUSAN, etc. and a KLT proposed for extracting the above-mentioned feature points. Refer to the following patent documents 1 through 6 for operators.
It is necessary to associate images with each other with high accuracy when a panoramic image is generated, the resolution of an image is enhanced, noise is to be reduced, etc. by combining a plurality of images. However, with increasing complexity of arithmetic operations on multi-pixel images to be processed after the improvement of performance of a digital camera etc., a high-speed processing method is demanded.
The following patent documents relate to the conventional image combining methods. The patent document 1 discloses a technique of matching images by a wavelet variable template matching method. The patent document 2 discloses a camera shake correcting method using low-resolution images. The patent document 3 discloses a technique of extracting and associating feature points of graphic data with each other at each hierarchical level corresponding to the resolution of a display device when the graphic data is displayed. The patent document 4 discloses a technique of an image reconstruction apparatus using the positions and shapes of feature points having different resolutions.    Patent Document 1: Japanese Patent Application Publication No. 2001-34756    Patent Document 2: Japanese Patent Application Publication No. 2004-343483    Patent Document 3: Japanese Patent Application Publication No. H8-87585    Patent Document 4: Japanese Patent No. 2652070    Patent Document 5: Japanese Patent Application Publication No. H10-83442    Non-patent Document 1: Bruce D. Lucas and Takeo Kanade: “An Iterative Image Registration Technique with an Application to Stereo Vision”, International Joint conference on Artificial Intelligence, pages 674-679, 1981.    Non-patent Document 2: Carlo Tomasi and Takeo Kanade: “Detection and Tracking of Point Features.”, Carnegie Mellon University Technical Report CMU-CS-91-132, April 1991.    Non-patent Document 3: Hideyuki Tamura: “Computer Image Processing”, Ohmusha, ISBN 4-274-13264-1    Non-patent Document 4: C. Harris and M. Stephens: “A combined Corner and Edge Detector”, Proc. Alvey Vision Conf. pp. 147-151, 1988    Non-patent Document 5: S. M. Smith, J. M. Brady: “SUSAN-A New Approach to Low Level Image Processing”    Non-patent Document 6: Richard Hartley, Andrew Zisserman: “Multiple View Geometry in Computer Vision” Campridge Univ Pr (Txp); ISBN: 0521540518; 2nd (2004 Apr. 1)